Multiple Prey Agent

Multiple prey agent research focuses on understanding and modeling the complex interactions between multiple prey animals attempting to evade a predator, often within simulated environments. Current research utilizes multi-agent reinforcement learning, particularly parameter-sharing architectures, to improve coordination and efficiency among prey agents, and employs deep learning for visual detection and analysis of predator-prey interactions in real-world scenarios like underwater video analysis of penguin hunting. This work contributes to a deeper understanding of ecological dynamics and informs the development of advanced algorithms for autonomous systems, such as robot control and object detection in challenging conditions.